A decade ago, “Big Data” was still a pretty vague term. But a lot has changed since then. The concept has become an important part of the digital advertising industry. So much so, that data is considered its ‘currency’. The success of many businesses and their ability to stay relevant and competitive is determined by their preparedness to collect and analyze data. We’re talking gigantic amounts of it. And the benefits it brings are significant.
How it all works and what it does, we’re here to learn more. Let’s talk about what Big Data is and how it’s been shaping the ad tech industry.
What is Big Data?
Big Data is a term that describes large amounts of information, both structured and unstructured, that needs advanced technology to be processed and analyzed.
We all know that users generate data all the time by carrying out simple tasks: browsing the internet, shopping online, using mobile applications, etc. Some of this data is structured, which means it consists of clearly defined data types with patterns that make it searchable. On the other hand, a lot of the data is ‘chaotic’. That’s qualitative data that hasn’t been structured using a predefined model. It comprises up to 80% of all data and includes images, videos, social media posts, etc. that are hard to manage. However, the use of new technology such as artificial intelligence has made it possible to harness it. This way, companies have access to more and new types of data to make informed, data-driven decisions.
In other words, Big Data describes the collection and analysis of large volumes of data using advanced methods. But more importantly, it’s about how companies use Big Data to better understand their customers and how it affects their strategies.
How is it used?
Analyzing Big Data can help companies learn things like: What audience to target? How to customize digital ads? How to track results? And most importantly, how to use this info to make relevant business decisions? Read below to find out more about Big Data’s role in answering these important questions.
Using Big Data, companies can segment their target audience into different groups. Your approach depends on the type of product or service you offer. In general, there are four methods of audience segmentation:
- Demographic (age, gender, education, gender, race, income, religion, marital status, etc.)
- Geographic (country, region, city, district or urban/suburban/rural)
- Behavioral (online purchasing habits, what actions people take online, for how long, how frequently they buy your product, how loyal they are to the brand, etc.)
- Psychographic (traits, hobbies, interests, values, beliefs, attitudes, preferences, etc.)
This way, instead of trying to come up with a universal message to appeal to everyone, marketers can tailor it to make it more relevant to each subgroup. Data even allows Dynamic Creative Optimization (a.k.a. “dynamic ads”) where an ad’s message is tweaked in real-time by picking a different combination of media, text, etc. And more personalized ads mean improved overall ad campaign performance.
Ad measurement and attribution are important in determining how successful conversion is across different channels. For example, data-driven attribution models follow how the customer responded to an advertisement. This helps companies get a grasp of how exactly people convert, which channels and ads work best, etc. This, in turn, allows for greater transparency and budget optimization.
It’s all about data-driven decision-making. Big data analytics platforms allow companies to capture, store and analyze the data they’ve gathered. Many use open-source Big Data tools as their framework of choice. Data science experts, in turn, cleanse the data, interpret it, find patterns, and develop models. All in order to extract actionable insights. These inform decisions and shape marketing strategies. They can reveal untapped audience segments and opportunities for new product development. They may even help build a better brand identity and improve business focus.
Over the years, Big Data has become an important part of marketing and advertising. Companies have learned to collect, store and use it. Simultaneously, users have come to expect relevant ads. So using the power of Big Data, businesses run more targeted ad campaigns and build a better relationship with their audience, while their strategic decisions are more cost-effective and data-driven.